We are looking for a skilled Data Engineer to design and implement robust technical solutions for enterprise applications. This role involves creating scalable and secure cloud-native systems on Azure, while collaborating closely with stakeholders to meet business requirements. The ideal candidate will possess strong expertise in data architecture and integration strategies, ensuring high engineering standards and seamless orchestration across systems.<br><br>Responsibilities:<br>• Design and maintain comprehensive technical architectures for enterprise applications, ensuring scalability and security.<br>• Develop integration strategies across multiple systems, including manufacturing, field service, and customer portals.<br>• Collaborate with the Principal Architect to define data contracts and establish effective integration patterns.<br>• Partner with teams in Product, AI/ML Engineering, and business units to translate requirements into functional solutions.<br>• Create reference implementations and frameworks to streamline development processes.<br>• Oversee system-level orchestration and elevate engineering standards across projects.<br>• Implement cloud-native solutions on Azure, leveraging modern tools and technologies.<br>• Provide technical guidance and mentorship to engineering teams, fostering best practices.<br>• Continuously monitor and improve system performance, addressing issues proactively.
We are looking for an experienced Lead Data Engineer to oversee the design, implementation, and management of advanced data infrastructure in Houston, Texas. This role requires expertise in architecting scalable solutions, optimizing data pipelines, and ensuring data quality to support analytics, machine learning, and real-time processing. The ideal candidate will have a deep understanding of Lakehouse architecture and Medallion design principles to deliver robust and governed data solutions.<br><br>Responsibilities:<br>• Develop and implement scalable data pipelines to ingest, process, and store large datasets using tools such as Apache Spark, Hadoop, and Kafka.<br>• Utilize cloud platforms like AWS or Azure to manage data storage and processing, leveraging services such as S3, Lambda, and Azure Data Lake.<br>• Design and operationalize data architecture following Medallion patterns to ensure data usability and quality across Bronze, Silver, and Gold layers.<br>• Build and optimize data models and storage solutions, including Databricks Lakehouses, to support analytical and operational needs.<br>• Automate data workflows using tools like Apache Airflow and Fivetran to streamline integration and improve efficiency.<br>• Lead initiatives to establish best practices in data management, facilitating knowledge sharing and collaboration across technical and business teams.<br>• Collaborate with data scientists to provide infrastructure and tools for complex analytical models, using programming languages like Python or R.<br>• Implement and enforce data governance policies, including encryption, masking, and access controls, within cloud environments.<br>• Monitor and troubleshoot data pipelines for performance issues, applying tuning techniques to enhance throughput and reliability.<br>• Stay updated with emerging technologies in data engineering and advocate for improvements to the organization's data systems.
